| The initial project file can be downloaded from [This Link](https://codern.org/qbox/download/8kPk3LDPT9/initial.zip).| | :--: | HonkHonk is a successful ride-hailing company focused in New York City. This company has spent nearly a decade researching and improving the accuracy and logic of its trip pricing system. The result of these efforts is a dynamic pricing function with 3,500 lines of code. The code for this function is highly confidential and sensitive. For this reason, only one copy of it was stored on a private server held by the CEO. The CEO kept this server under his desk to ensure everyone's peace of mind. One day, while the CEO was drinking tea, an unfortunate incident occurred: the CEO's cup of tea spilled, burning the server and wiping out the data within it. Now, to prevent the company from going bankrupt, the CEO has decided to build a new system to replace the previous pricing function. Therefore, he urgently needs your help to overcome this challenge. Only the following sentence regarding how the previous pricing function worked is available: > This function provided dynamic pricing. Trip prices were calculated based on temporal factors, location, weather, and more. After much effort, the CEO managed to prepare a highly valuable dataset of trips conducted by HonkHonk over several consecutive months in 2016 in New York City, where the original pricing function determined the trip cost, and has provided it to you. Furthermore, to evaluate the quality of your proposed system, the CEO has kept a portion of this dataset to ensure the quality of your output. <details class="yellow"> <summary>**Dataset**</summary> | Column Name | Description | | :----------------------: | :-----------------------------: | | `id` | A unique identifier for each trip. | | `pickup_datetime` | Date and time the trip started. | | `dropoff_datetime` | Date and time the trip ended. | | `passenger_count` | Number of passengers in the vehicle. | | `pickup_longitude` | Longitude of the trip origin location. | | `pickup_latitude` | Latitude of the trip origin location. | | `dropoff_longitude` | Longitude of the trip destination location. | | `dropoff_latitude` | Latitude of the trip destination location. | | `store_and_fwd_flag` | Indicates whether the trip information was stored in the vehicle's memory before being sent to the server. (Y/N) | | `trip_duration` | Total trip duration in seconds. | | `total_price` | **(Target Variable)** The final and total trip price in dollars (only available in `train.csv`). | </details> Your mission is to design a dynamic pricing system for HonkHonk using this dataset, along with programming techniques, artificial intelligence, machine learning, and by gathering necessary auxiliary data. **Are you ready for this mission?!** ## Evaluation Metric This scoring system compares your model’s error (RMSE) against the **Standard Deviation** of the true values (`std(Y_true)`). The standard deviation measures the inherent variability or fluctuation in the traffic data. Therefore, a successful model must not only be accurate but also have an error that is small relative to these natural variations. \[ Score = 100 \times e^{\left(-\frac{\text{RMSE}}{\text{std}(Y_{\text{true}})}\right)} \] A score of 100 indicates a perfectly accurate prediction (zero error). This formula works exponentially — meaning that models whose errors are much smaller than the natural fluctuations in the data receive high scores, while scores drop rapidly as the error increases. <details class="red"> <summary> **Attention** </summary> Throughout the competition, the score you see is only the result of evaluating your model on 30 percent of the test data. After the competition ends, your **final score** will be calculated on the remaining 70 percent. This is done to prevent overfitting and maintain the generality of the model, ensuring that models that have overfitted will drop in the final scoring. </details> ## Submission Method To answer this question, first open the notebook file included in the initial file and then follow the steps as requested. Finally, after executing the answer-generating cell (the last cell of the notebook file), submit the created `result.zip` file. <details class="red"> <summary> **Important Warning** </summary> Note that you must save the changes made in the notebook using the shortcut key `ctrl+s` before executing the answer-generating cell; otherwise, your **score** will change to **zero** at the end of the competition. Also, if you use Colab to run this notebook file, download the latest version of your notebook and include it in the submitted file before sending the `result.zip` file. </details>